}

#endif  // LIBTPU_EXCLUDE_C_API_IMPL

namespace tensorflow {

void TensorInterface::Release() {
  if (Type() == DT_STRING && NumElements() > 0) {
    TF_TString* data = static_cast<TF_TString*>(Data());
    if (CanMove() && data != nullptr) {
      for (int64_t i = 0; i < NumElements(); ++i) {
        TF_TString_Dealloc(&data[i]);
      }
    }
  }
  delete this;
}

                                             Tensor* device_tensor,
                                             StatusCallback done,
                                             bool sync_dst_compute) const {
  if (cpu_tensor->NumElements() == 0) {
    VLOG(2) << "CopyCPUTensorToDevice empty tensor";
    done(absl::OkStatus());
    return;
  }

  VLOG(2) << "CopyCPUTensorToDevice " << this << " "

      typedef typename RealType<T>::type RealT;
      Tensor t(DataTypeToEnum<RealT>::v(), shape);
      if (t.NumElements() != static_cast<int64_t>(v.size())) {
        status = absl::InvalidArgumentError(absl::StrCat(
            "Cannot construct a tensor with ", t.NumElements(),
            " from an initializer list with ", v.size(), " elements"));
        return;
      }

                                              StatusCallback done) {
  tsl::profiler::TraceMe traceme("PjRtDeviceContext::CopyDeviceTensorToCPU");
  if (device_tensor->NumElements() == 0) {
    VLOG(2) << "CopyDeviceTensorToCPU empty tensor";
    done(absl::OkStatus());
    return;
  }
  auto literal = std::make_unique<xla::MutableBorrowingLiteral>();

  mlir::MLIRContext context;
  RegisterDialects(context);
  mlir::Builder b(&context);

  // Create the sample tensor to convert.
  Tensor tensor(DT_STRING, TensorShape({1, 2, 2, 1}));
  EXPECT_EQ(4, tensor.NumElements());
  auto Tt = tensor.flat<tstring>();
  Tt.setValues({"one", "two", "three", "four"});
  auto value_or_status = ConvertTensor(tensor, &b);
  ASSERT_TRUE(value_or_status.ok());
  auto attr = value_or_status.value();